State-dependent modulation of cross-area sensory processing in mouse neocortex

Perception and decision-making rely on distributed cortical circuits that transform sensory inputs into choices and actions. Such cortical processing varies with behavioral state, such that the same inputs can be handled differently across states. However, how behavioral state shapes sensory processing across distributed brain regions remains unclear. To address this question, we trained mice to perform a two-alternative choice task that required discrimination between paired auditory and whisker cues. During task training, we simultaneously recorded neuronal population activity from the primary somatosensory cortex (S1) and the posterior parietal cortex (PPC), using two-photon imaging of neurons expressing the fluorescent calcium indicator GCaMP6f. Using a Hidden Markov Model with Generalized Linear Models (GLM-HMM), we identified three latent behavioral states, including one optimal-performing stimulus-guided state and two sub-optimal biased states. We found that the optimal state was associated with stronger sensory representation in S1 and PPC, as well as stronger bottom-up information transfer from S1 to anterior PPC (PPC-A). In contrast, biased states showed weaker sensory coding and relatively stronger involvement of rostrolateral PPC (PPC-RL). State-dependent differences were present in both task-related and task-orthogonal population activity. These results show that internal states modulate not only local sensory encoding, but also the routing of task-relevant information across cortical networks.